全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...
PLOS ONE  2013 

Waist-to-Height Ratio and Cardiovascular Risk Factors among Chinese Adults in Beijing

DOI: 10.1371/journal.pone.0069298

Full-Text   Cite this paper   Add to My Lib

Abstract:

Objectives To examine whether waist-to-height ratio (WHtR) performed better than, body mass index (BMI) or waist circumference (WC) in relation to hypertension, diabetes, and dyslipidemia among Chinese adults in Beijing. Methods A total of 5720 adults (2371 men and 3349 nonpregnant women) aged 18 to 79 years were selected from the general population in a cross-sectional study. Data from a standardized questionnaire, physical examination, and blood sample were obtained. Results The area under curve (AUC) values for WHtR (0.661–0.773) were significantly higher than those for BMI for all outcomes in both sexes, except that WHtR and BMI had similar AUCs for dyslipidemia in men. The AUCs for WHtR were significantly higher than those for WC with respect to hypertension in both sexes, and to diabetes in women. AUCs for the relationships between anthropometric indices and the three outcomes were larger in women than in men, and tended to decrease with age. Optimal cutoffs for WHtR were 0.51–0.53 and 0.48–0.50 in men and women, respectively. With regard to the current Chinese criteria for BMI (≥24 kg/m2), WC (≥90 cm for men, and ≥85 cm for women), and the recommended cutoff of WHtR (≥0.5), WHtR yielded the greatest odds ratio for hypertension and diabetes in both sexes, and dyslipidemia in women. BMI had the highest odds ratio for dyslipidemia in men. The odds ratios of anthropometric indices for hypertension and diabetes, but not for dyslipidemia, were higher in women than in men. The association between anthropometric indices and the three outcomes decreased with age. Conclusion WHtR performed better than BMI and WC for the association with hypertension and diabetes. More studies should be conducted to explore the age differences in the relationships between obesity indices and cardiovascular risk factors.

References

[1]  Visscher TL, Seidell JC (2001) The public health impact of obesity. Annu Rev Public Health 22: 355–75.
[2]  Klein S, Allison DB, Heymsfield SB, Kelley DE, Leibel RL, et al. (2007) Waist circumference and cardiometabolic risk: a consensus statement from Shaping America's Health: Association for Weight Management and Obesity Prevention; NAASO, The Obesity Society; the American Society for Nutrition; and the American Diabetes Association. Am J Clin Nutr 85: 1197–202.
[3]  Despres JP (2001) Health consequences of visceral obesity. Ann Med 33: 534–41.
[4]  Lemieux I, Poirier P, Bergeron J, Almeras N, Lamarche B, et al. (2007) Hypertriglyceridemic waist: a useful screening phenotype in preventive cardiology? Can J Cardiol 23 Suppl B:23B–31B.
[5]  Ashwell M, Gunn P, Gibson S (2012) Waist-to-height ratio is a better screening tool than waist circumference and BMI for adult cardiometabolic risk factors: systematic review and meta-analysis. Obes Rev 13: 275–86.
[6]  Dong X, Liu Y, Yang J, Sun Y, Chen L (2011) Efficiency of anthropometric indicators of obesity for identifying cardiovascular risk factors in a Chinese population. Postgrad Med J 87: 251–56.
[7]  Kodama S, Horikawa C, Fujihara K, Heianza Y, Hirasawa R, et al. (2012) Comparisons of the Strength of Associations With Future Type 2 Diabetes Risk Among Anthropometric Obesity Indicators, Including Waist-to-Height Ratio: A Meta-Analysis. Am J Epidemiol 176: 959–69.
[8]  Vazquez G, Duval S, Jacobs DJ, Silventoinen K (2007) Comparison of body mass index, waist circumference, and waist/hip ratio in predicting incident diabetes: a meta-analysis. Epidemiol Rev 29: 115–28.
[9]  Wakabayashi I (2012) Stronger associations of obesity with prehypertension and hypertension in young women than in young men. J Hypertens 30: 1423–29.
[10]  Browning LM, Hsieh SD, Ashwell M (2010) A systematic review of waist-to-height ratio as a screening tool for the prediction of cardiovascular disease and diabetes: 0.5 could be a suitable global boundary value. Nutr Res Rev 23: 247–69.
[11]  Joint Committee for Developing Chinese guidelines on prevention and treatment of dyslipidemia in adults (2007) Chinese guidelines on prevention and treatment of dyslipidemia in adults. Chin J Cardiol 35: 390–419.
[12]  Cai L, Zhang L, Liu A, Li S, Wang P (2012) Prevalence, awareness, treatment, and control of dyslipidemia among adults in Beijing, China. J Atheroscler Thromb 19: 159–68.
[13]  DeLong ER, DeLong DM, Clarke-Pearson DL (1988) Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 44: 837–45.
[14]  Wu Y, Huxley R, Li L, Anna V, Xie G, et al. (2008) Prevalence, awareness, treatment, and control of hypertension in China: data from the China National Nutrition and Health Survey 2002. Circulation 118: 2679–86.
[15]  Tseng CH, Chong CK, Chan TT, Bai CH, You SL, et al. (2010) Optimal anthropometric factor cutoffs for hyperglycemia, hypertension and dyslipidemia for the Taiwanese population. Atherosclerosis 210: 585–89.
[16]  Ho SY, Lam TH, Janus ED (2003) Waist to stature ratio is more strongly associated with cardiovascular risk factors than other simple anthropometric indices. Ann Epidemiol 13: 683–91.
[17]  Park SH, Choi SJ, Lee KS, Park HY (2009) Waist circumference and waist-to-height ratio as predictors of cardiovascular disease risk in Korean adults. Circ J 73: 1643–50.
[18]  Lee CM, Huxley RR, Wildman RP, Woodward M (2008) Indices of abdominal obesity are better discriminators of cardiovascular risk factors than BMI: a meta-analysis. J Clin Epidemiol 61: 646–53.
[19]  Ashwell M, Hsieh SD (2005) Six reasons why the waist-to-height ratio is a rapid and effective global indicator for health risks of obesity and how its use could simplify the international public health message on obesity. Int J Food Sci Nutr 56: 303–07.
[20]  Jia Z, Zhou Y, Liu X, Wang Y, Zhao X, et al. (2011) Comparison of different anthropometric measures as predictors of diabetes incidence in a Chinese population. Diabetes Res Clin Pract 92: 265–71.
[21]  He Y, Zhai F, Ma G, Feskens EJ, Zhang J, et al. (2009) Abdominal obesity and the prevalence of diabetes and intermediate hyperglycaemia in Chinese adults. Public Health Nutr 12: 1078–84.
[22]  Shimajiri T, Imagawa M, Kokawa M, Konami T, Hara H, et al. (2008) Revised optimal cut-off point of waist circumference for the diagnosis of metabolic syndrome in Japanese women and the influence of height. J Atheroscler Thromb 15: 94–99.
[23]  Wu H, Zhu Q, Gu J, Yuan X, Xu W, et al. (2010) A cross-sectional study on the relationship between anthropometric indices and blood pressures among the residents of Pudong New Area of Shangha. Fudan Univ J Med Sci 4: 401–08.
[24]  Wang JW, Hu DY, Sun YH, Wang JH, Wang GL, et al. (2009) Obesity criteria for identifying metabolic risks. Asia Pac J Clin Nutr 18: 105–13.
[25]  Wakabayashi I, Daimon T (2011) Receiver-operated characteristics (ROCs) of the relationships between obesity indices and multiple risk factors (MRFs) for atherosclerosis at different ages in men and women. Arch Gerontol Geriatr.
[26]  Doherty TJ (2001) The influence of aging and sex on skeletal muscle mass and strength. Curr Opin Clin Nutr Metab Care 4: 503–08.
[27]  Cnop M, Havel PJ, Utzschneider KM, Carr DB, Sinha MK, et al. (2003) Relationship of adiponectin to body fat distribution, insulin sensitivity and plasma lipoproteins: evidence for independent roles of age and sex. Diabetologia 46: 459–69.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133